Analyzing the factors affecting environmental risks of projects using a hybrid approach of DEMATEL‐ANP,artificial neural network: A case study

The increasing growth of the economy in each country necessitates a great amount of investment in infrastructure. The belief that projects involve various uncertainties, such as technical skills, management quality, and the like, indicates that most projects fail to achieve their aims, interests, costs, as well as their timeframes and space requirements. As the environment can pose significant uncertainty to any project, environmental risks should be deeply studied by project management departments. This study intends to analyze as a case the environmental risk management system within a consulting firm. From this analysis, each aspect of a project's environmental risk management is ranked using a fuzzy analytical network process (ANP), a neural network algorithm, and a decision‐making trial and evaluation laboratory (DEMATEL) methodology. From the organizational aspect, budget risk is the most significant. From the technical aspect, the risk of regulations is the most important one. Finally, the risk of project failure from poor communication is another identified main risk in this research. By studying high‐ranking items in this hierarchy, it can be understood that these criteria exist in different aspects; therefore, all aspects of the risk should be taken into account to cover and assess risk. A neural network algorithm for validating and reassessment of ranking is employed. Results of this application showed that, based on Spearman's rank correlation method, two different approaches resulted in similar rankings. Finally, some practical implications for responding to the most highly ranked risks are proposed.     

A distance-based uncertainty analysis approach to multi-criteria decision analysis for water resource decision making

The choice among alternative water supply sources is generally based on the fundamental objective of maximising the ratio of benefits to costs. There is, however, a need to consider sustainability, the environment and social implications in regional water resources planning, in addition to economics. In order to achieve this, multi-criteria decision analysis (MCDA) techniques can be used. Various sources of uncertainty exist in the application of MCDA methods, including the selection of the MCDA method, elicitation of criteria weights and assignment of criteria performance values. The focus of this paper is on the uncertainty in the criteria weights. Sensitivity analysis can be used to analyse the effects of uncertainties associated with the criteria weights. Two existing sensitivity methods are described in this paper and a new distance-based approach is proposed which overcomes limitations of these methods. The benefits of the proposed approach are the concurrent alteration of the criteria weights, the applicability of the method to a range of MCDA techniques and the identification of the most critical criteria weights. The existing and proposed methods are applied to three case studies and the results indicate that simultaneous consideration of the uncertainty in the criteria weights should be an integral part of the decision making process.     

Dealing with uncertainty in collaborative planning: developing adaptive strategies for the IJsselmeer

Adaptive strategies to deal with uncertainty in water management are often collaboratively developed. So far, however, little attention has been paid to the influence of collaboration on handling uncertainty through adaptive planning. In this paper, we study how collaboration has influenced the handling of uncertainty through adaptive planning for water management strategies for the IJsselmeer area in the Netherlands. We show how a fixation on certainty, different perspectives among actors and unclear responsibilities between arenas affect the handling of uncertainty, and found that it is adversely affected by collaboration. The use of adaptive planning challenged current water uses and system functions, creating resistance from actors. We conclude that developing a shared problem perception, creating a common understanding of uncertainties and ensuring a clear demarcation between the water system, its societal functions and water usage, are necessary to make adaptive planning successful in handling uncertainty.     

Fusing strategic risk and futures methods to inform long-term strategic planning: case of water utilities

Risks and futures methods have complementary strengths as tools for managing strategic decisions under uncertainty. When combined, these tools increase organisational competency to evaluate and manage long-term risks, improving the flexibility and agility of the organisation to deal with gross uncertainties. Here, we set out a framework to guide the assessment of strategic risks for long-term business planning, based on its application at Portugal’s largest water utility, Empresa Portuguesa das Águas Livres. Our approach extends strategic risk assessment by incorporating scenario planning—a futures approach used to help the utility move beyond single point forecast of risks to focus on critical dimensions of uncertainty that are fundamental to the resilience of corporate objectives and their vulnerability to external pressures. We demonstrate how we combine two complementary approaches—risk and futures—and use them to assess (i) how a set of baseline strategic risks for a water utility evolves under alternative futures, (ii) the aggregate corporate-level risk exposure, and (iii) the process and responses needed to manage multiple, interdependent strategic risks. The framework offers a corporate approach to evolving strategic risks and improves a utility’s (i) knowledge of uncertainties, (ii) ability to assess the impacts of external developments over long time horizons and the consequences of actions and (iii) degree of flexibility to adapt to possible future challenges. The framework supports risk managers in their long-term strategic planning, through the appraisal and management of multiple, interdependent long-term strategic risks and can be replicated in other organisational contexts to bridge operational and corporate perspectives of enterprise risk.

     

基于价值创造视角的公司水风险管理研究

随着全球水资源供应不确定性与需求竞争性的加剧,水资源问题已从单纯的环境问题转化为经济问题,水风险逐渐与商业风险挂钩,公司面临的水风险不断上升。公司面临着物理风险、监管风险和声誉风险等水风险,公司水价值体现在业务连续性、经营牌照、声誉与品牌价值和创新价值等无形资产中。水风险与水价值二者相互联系又相互影响,通过公司水价值与水风险评估框架,了解区分水价值的不同方法,明确风险和不确定性如何影响水的价值,并利用水工具评估和管理公司所面临的水风险以及水对公司价值的影响,帮助公司化解其所面临的水风险,实现从公司水风险管理到价值创造的转变。     

Water Management Decision Making in the Face of Multiple Forms of Uncertainty and Risk

In the Wasatch Range Metropolitan Area of Northern Utah, water management decision makers confront multiple forms of uncertainty and risk. Adapting to these uncertainties and risks is critical for maintaining the long‐term sustainability of the region's water supply. This study draws on interview data to assess the major challenges climatic and social changes pose to Utah's water future, as well as potential solutions. The study identifies the water management adaptation decision‐making space shaped by the interacting institutional, social, economic, political, and biophysical processes that enable and constrain sustainable water management. The study finds water managers and other water actors see challenges related to reallocating water, including equitable water transfers and stakeholder cooperation, addressing population growth, and locating additional water supplies, as more problematic than the challenges posed by climate change. Furthermore, there is significant disagreement between water actors over how to best adapt to both climatic and social changes. This study concludes with a discussion of the path dependencies that present challenges to adaptive water management decision making, as well as opportunities for the pursuit of a new water management paradigm based on soft‐path solutions. Such knowledge is useful for understanding the institutional and social adaptations needed for water management to successfully address future uncertainties and risks.     

Multi-criteria risk management with the use of <Emphasis Type="Italic">DecernsMCDA</Emphasis>: methods and case studies

Emerging challenges of risk management, environmental protection, and land-use planning requires integration of stakeholder values and expert judgment. The process of decision making in situation of high uncertainty can be assisted through the use of decision support systems (DSSs). Such DSSs are often based on tools for spatial data representation (GIS) and environmental models that are integrated using multi-criteria decision analysis (MCDA). This paper presents DecernsMCDA implementing all major types of multi-criteria methods and tools (AHP, MAUT, Outranking) under the same user interface. In addition to providing ability for testing model uncertainty associated with selection of specific MCDA algorithms, DecernsMCDA implements new algorithms for parameter uncertainty analysis based on probabilistic approaches and fuzzy sets. The paper illustrates application of DecernsMCDA for selecting remedial alternative at radiologically contaminated sites.     

COMPUTING THE RISKS ASSOCIATED WITH WASTELOAD) ALLOCATION MODELING1

ABSTRACT: The risks associated with a traditional wasteload allocation (WLA) analysis were quantified with data from a recent study of the Upper Trinity River (Texas). Risk is define here as the probability of failing to meet an established in-stream water quality standard. The QUAL-TX dissolved oxygen (DO) water quality model was modified to a Monte Carlo framework. Flow augmentation coding was also modified to allow an exact match to be computed between the predicted and an established DO concentration standard, thereby providing an avenue for linking input parameter uncertainty to the assignment of a wasteload permit (allowable mass loading rate). Monte Carlo simulation techniques were employed to propagate input parameter uncertainties, typically encountered during WLA analysis, to the computed effluent five-day carbonaceous biochemical oxygen demand requirements for a single major wastewater treatment plant (WWTP). The risk of failing to meet an established in-stream DO criterion may be as high as 96 percent. The uncertainty associated with estimation of the future total Kjeldahl nitrogen concentration for a single tributary was found to have the greatest impact on the determination of allowable WWTP loadings.     

Uncertainty and risk in wildland fire management: a review

Wildland fire management is subject to manifold sources of uncertainty. Beyond the unpredictability of wildfire behavior, uncertainty stems from inaccurate/missing data, limited resource value measures to guide prioritization across fires and resources at risk, and an incomplete scientific understanding of ecological response to fire, of fire behavior response to treatments, and of spatiotemporal dynamics involving disturbance regimes and climate change. This work attempts to systematically align sources of uncertainty with the most appropriate decision support methodologies, in order to facilitate cost-effective, risk-based wildfire planning efforts. We review the state of wildfire risk assessment and management, with a specific focus on uncertainties challenging implementation of integrated risk assessments that consider a suite of human and ecological values. Recent advances in wildfire simulation and geospatial mapping of highly valued resources have enabled robust risk-based analyses to inform planning across a variety of scales, although improvements are needed in fire behavior and ignition occurrence models. A key remaining challenge is a better characterization of non-market resources at risk, both in terms of their response to fire and how society values those resources. Our findings echo earlier literature identifying wildfire effects analysis and value uncertainty as the primary challenges to integrated wildfire risk assessment and wildfire management. We stress the importance of identifying and characterizing uncertainties in order to better quantify and manage them. Leveraging the most appropriate decision support tools can facilitate wildfire risk assessment and ideally improve decision-making.     

化工区风险源的灰色聚类分级方法的研究

建设化工区需对企业进行合理规划布局,且化工区风险预警和防范具有优先性问题,需要对企业进行有效的风险分级。现有研究中的区域风险源分级方法上存在较大的不足。根据化工区风险源的特点,基于环境风险评价和灰色系统的基本理论,探索性的将灰色聚类分析方法应用于化工区风险源分级中。建立了一套适合化工园区的指标,对各个企业进行聚类分析,划分风险等级。以大连市某化工区为例,筛选8个指标,并选取了6个化工企业进行灰色聚类分析。将它们归为4个不同的风险级别。该方法不仅能较全面地反映化工区各个风险源的风险级别,对风险源的规划、布局和管理起到较好的决策支持作用,而且能指导预警和防范体系的建立,合理分配有限的资源。     

Making framing of uncertainty in water management practice explicit by using a participant-structured approach

By now, the need for addressing uncertainty in the management of water resources is widely recognized, yet there is little expertise and experience how to effectively deal with uncertainty in practice. Uncertainties in water management practice so far are mostly dealt with intuitively or based on experience. That way decisions can be quickly taken but analytic processes of deliberate reasoning are bypassed. To meet the desire of practitioners for better guidance and tools how to deal with uncertainty more practice-oriented systematic approaches are needed. For that purpose we consider it important to understand how practitioners frame uncertainties. In this paper we present an approach where water managers developed criteria of relevance to understand and address uncertainties. The empirical research took place in the Doñana region of the Guadalquivir estuary in southern Spain making use of the method of card sorting. Through the card sorting exercise a broad range of criteria to make sense of and describe uncertainties was produced by different subgroups, which were then merged into a shared list of criteria. That way framing differences were made explicit and communication on uncertainty and on framing differences was enhanced. In that, the present approach constitutes a first step to enabling reframing and overcoming framing differences, which are important features on the way to robust decision-making. Moreover, the elaborated criteria build a basis for the development of more structured approaches to deal with uncertainties in water management practice.     

Building Consensus in Environmental Impact Assessment Through Multicriteria Modeling and Sensitivity Analysis

Multicriteria decision analysis (MCDA) increasingly is being applied in environmental impact assessment (EIA). In this article, two MCDA techniques, stochastic analytic hierarchy process and compromise programming, are combined to ascertain the environmental impacts of and to rank two alternative sites for Mexico City’s new airport. Extensive sensitivity analyses were performed to determine the probability of changes in rank ordering given uncertainty in the hierarchy structure, decision criteria weights, and decision criteria performances. Results demonstrate that sensitivity analysis is fundamental for attaining consensus among members of interdisciplinary teams and for settling debates in controversial projects. It was concluded that sensitivity analysis is critical for achieving a transparent and technically defensible MCDA implementation in controversial EIA.     

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.     

Public and occupational risks of the Nevada (USA) Test Site

The Nevada Test Site (NTS), north of Las Vegas, was the scene of hundreds of nuclear weapons tests over four decades, both above- and belowground. There is considerable interest, both in neighboring communities and elsewhere, in the risks it poses. Overall, the greatest risks are nonradioactive in origin, with occupational risks to employees and accident risks in transporting low-level nuclear wastes to the NTS from other Department of Energy (DOE) sites ranking highest. For radiation risks, that to workers handling radioactive materials is much higher than that to the surrounding population, either present or future. Overall, annual risks are small, with all fatalities approximately 0.008% of total Nevada deaths. At the NTS, the government spends about 5000 times more on radiation as opposed to nonradiation deaths. This suggests that at least some resources may be misallocated towards cleanup of public risks and that the occupational risk of cleanup may be much higher than the public risk. Thus risk may be multiplied by well-meaning programs.     

TMDL中MOS的定量估算方法及其应用

为了分析TMDL水污染控制管理模式中安全临界值MOS的影响因素,采用FOEA法对MOS中模拟计算的不确定性进行定量估算,通过不同水质达标率条件下MOS的设定,探讨水环境管理中不确定性因素对MOS的影响;将TMDL应用于珠江三角洲佛山水道的水环境管理中,运用动态水环境数学模型、考虑潮周期达标率的环境容量优化模型及遗传算法对TMDL进行求解.研究结果表明,所采用的FOEA法能较为准确地反映模型的不确定性对MOS的影响,而且从水质达标率的角度出发能合理地考察环境管理中的不确定性因素对MOS的影响,为定量化探讨MOS的设定给出了可行的求解思路及方法.     

Relative cancer risks of chemical contaminants in the great lakes

Anyone who drinks water or eats fish from the Great Lakes consumes potentially carcinogenic chemicals. In choosing how to respond to such pollution, it is important to put the risks these contaminants pose in perspective. Based on recent measurements of carcinogens in Great Lakes fish and water, calculations of lifetime risks of cancer indicate that consumers of sport fish face cancer risks from Great Lakes contaminants that are several orders of magnitude higher than the risks posed by drinking Great Lakes water. But drinking urban groundwater and breathing urban air may be as hazardous as frequent consumption of sport fish from the Great Lakes. Making such comparisons is difficult because of variation in types and quality of information available and in the methods for estimating risk. Much uncertainty pervades the risk assessment process in such areas as estimating carcinogenic potency and human exposure to contaminants. If risk assessment is to be made more useful, it is important to quantify this uncertainty.     

Incorporating Uncertainty Into the Ranking of SPARROW Model Nutrient Yields From Mississippi/Atchafalaya River Basin Watersheds1

Abstract: Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient‐reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight‐digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.     

Contextualising risk within enterprise risk management through the application of systems thinking

New and emerging risks create growing uncertainty and unpredictability within enterprise risk management. While ISO 31000:2009 is a progressive risk management framework, it is limited in its guidance on how to contextualise complex risks. The application of systems thinking to risk management provides the opportunity to better understand complexity by viewing risk and the consequence of change as part of overall system behaviour. System modelling tools enable organisations to better contextualise their risk landscape. These tools assist organisations to identify vulnerabilities between social and ecological variables in the system within they exist. Determining drivers of change leading to system vulnerabilities can assist in understanding threshold limits of the system, thus enabling the organisation to build system resilience and organisational sustainability.     

Multicriteria Decision Aid in Supporting Decisions Related to Groundwater Protection

In the recent decades, there have been frequent conflicts between groundwater resources and environmentally hazardous activities. An example is the construction of the new highway through the important glaciofluvial esker aquifer Nybroåsen, which passes the protection zone of the water supply for the Kalmar municipality, in the southeastern part of Sweden. The decision to build the new road through this important aquifer has been strongly questioned by the municipality and the public because the value of the water resources in Nybroåsen was not taken into consideration during the first phase of the decision-making process. Multicriteria decision aid (MCDA) is applied as a tool to structure and analyze the four road alternatives proposed in the environmental impact assessment for the above conflict. The alternatives, including the existing road, are in conflict with water resources, agriculture, natural, and cultural values. The impacts on the water resources have been predicted by a two-dimensional physically based time-variant flow and solute groundwater model, which has been calibrated and evaluated. The MCDA illustrates how it can be used to identify (1) actors and their concerns, (2) ranking of alternative road scenarios according to actors preferences, and (3) coalition groups of actors, i.e., groups that have similar views with regard to the road alternatives. The analysis shows that the two best compromise solutions obtained in the MCDA were unacceptable by the strongest coalition group, showing that either the family of criteria was not well chosen or new alternatives should have been developed.